{
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   "metadata": {
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   },
   "source": [
    ".. _nb_g3pcx:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# G3PCX: A Computationally Efficient Evolutionary Algorithm for Real-Parameter Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The algorithm is implemented based on <cite data-cite=\"g3pcx\"></cite>.\n",
    "This is an implementation of PCX operator using G3 model. This is an unconstrained optimization algorithm which is suitable for real parameter optimization. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from pymoo.algorithms.soo.nonconvex.g3pcx import G3PCX\n",
    "from pymoo.problems.single import Ackley\n",
    "from pymoo.optimize import minimize\n",
    "\n",
    "problem = Ackley()\n",
    "\n",
    "algorithm = G3PCX()\n",
    "\n",
    "res = minimize(problem,\n",
    "               algorithm,\n",
    "               seed=1,\n",
    "               verbose=False)\n",
    "\n",
    "print(\"Best solution found: \\nX = %s\\nF = %s\" % (res.X, res.F))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### API"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    ".. autoclass:: pymoo.algorithms.soo.nonconvex.g3pcx.G3PCX\n",
    "    :noindex:\n",
    "    :no-undoc-members:"
   ]
  }
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